2019 Vol.2 Oct. No.5

• Title: Research on Interruptible Scheduling Algorithm of Central Air Conditioning Load under Big Data Analysis
• Name: Fakhri Alfredo
• Company: Russian St. Petersburg national university
• Abstract:

  The traditional algorithm is a combination of fuzzy dynamic programming and priority-based heuristic rules. The optimization performance of interruptible load scheduling is poor. For this reason, the central air conditioning load interruptible scheduling algorithm is proposed based on big data analysis. The algorithm adopts the characteristics of central air conditioning load management, selects the time scale of central air conditioning load scheduling, and optimizes the flexibility of interruptible scheduling. Based on the central air-conditioning load interruptible scheduling model, the optimal individual in the last-generation population is decoded by means of binary coding, so that the central air-conditioning load interruptible scheduling algorithm can be realized. The experiment proves that the central air conditioning load interruptible scheduling algorithm has strong optimization performance.

• Keyword: optimal scheduling strategy; time dimension; interrupt load; internal gene;
• DOI: 10.12250/jpciams2019050546
• Citation form: Fakhri Alfredo.Research on Interruptible Scheduling Algorithm of Central Air Conditioning Load under Big Data Analysis[J]. Computer Informatization and Mechanical System, 2019, vol. 2, pp. 67-73.

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